Build the data systems that power risk intelligence at scale.

Senior / Lead Data Engineer (AWS)

You will take technical ownership of data engineering on a long-term engagement — building reliable AWS-based pipelines, ensuring secure data handling in a PCI-regulated environment, and guiding two Data Engineers on the project.

A long-term engagement focused on building reliable data pipelines, improving engineering analytics, and ensuring secure data processing within a PCI-regulated environment. The client team is based in Portugal. The role is remote-first, with planned on-site visits in December 2026 and January/February 2027. The engagement starts at 50% allocation in December, transitioning to full-time from January 2027.

• Design and develop scalable data ingestion and processing pipelines using AWS
• Build baseline data extracts from CI/CD systems and Jira to support DORA and Flow Metrics
• Implement and maintain data provenance, lineage, and traceability across pipelines
• Prepare masked or synthetic datasets for secure testing
• Ensure compliant handling of sensitive data within a PCI environment
• Lead technical activities, review deliverables, and support two Data Engineers
• Collaborate with project stakeholders to ensure data quality, reliability, and security

• Strong hands-on Data Engineering experience at Senior or Lead level
• Solid experience with AWS data services and cloud-based data pipelines
• Strong Python and SQL skills
• Experience designing and developing ETL/ELT pipelines
• Understanding of data provenance, lineage, and data governance principles
• Experience with sensitive data handling, data masking, or synthetic test data generation
• Knowledge of data security and compliance requirements
• Ability to take technical ownership and provide guidance to other engineers
• Good English communication skills
• Based in Europe — availability for occasional business trips to Portugal required

• Experience integrating Jira and CI/CD systems (GitHub Actions, GitLab CI, Jenkins)
• Familiarity with DORA Metrics and Flow Metrics
• Previous experience in PCI DSS or other regulated environments
• Experience with AWS Glue, S3, Lambda, Redshift, or Step Functions
• Experience with Airflow or other workflow orchestration tools

• Dec 1, 2026 — Project start at 50% allocation
• Dec 14–18, 2026 — Initial on-site visit to Portugal
• Late Dec 2026 — Planned holiday pause
• Jan 4, 2027 — Project restart; planned transition to full-time (100%) allocation
• Jan / Early Feb 2027 — Second business trip to Portugal

Middle Data Engineer

You will build and maintain the ETL pipelines and Delta Lake data models that underpin a risk accumulation management platform at a major European insurance company.

The client is a major insurance company modernising their risk data infrastructure. You will join a data engineering team delivering a Lakehouse-based platform that centralises risk accumulation data across business lines and feeds actuarial and underwriting analytics.

• Develop and optimise ETL/ELT pipelines using Databricks and PySpark
• Build and maintain Delta Lake data models for risk accumulation reporting
• Migrate historical data from legacy systems into the Lakehouse architecture
• Implement data quality checks and monitoring across ingestion and transformation layers
• Collaborate with actuaries, underwriters, and business analysts to turn requirements into reliable data products

• 4+ years as a Data Engineer
• Hands-on experience with Databricks and Delta Lake
• Proficient in Python, PySpark, and advanced SQL
• Solid understanding of ETL/ELT design and data modelling
• Comfortable with Git and basic CI/CD workflows
• English B2–C1 — active communication with client stakeholders required

• Azure Data Services (Data Factory, Azure Storage, Azure SQL)
• Data governance or data cataloguing experience
• Background in insurance, financial services, or risk management

Senior Data Engineer

You will lead data architecture decisions and drive engineering delivery on a risk management platform for a major European insurance company.

The client is a major insurance company modernising their risk data infrastructure. As the senior engineer on the engagement, you will own the Lakehouse architecture, set pipeline standards, and serve as the primary technical contact for actuarial and underwriting stakeholders.

• Design and own the Delta Lake data model and Lakehouse architecture for risk accumulation reporting
• Lead ETL/ELT pipeline development and set engineering standards for the team
• Drive historical data migration strategy from legacy systems to Databricks
• Own PySpark transformation performance — tuning, optimisation, and production reliability
• Define and enforce data quality, governance, and monitoring practices
• Act as technical point of contact for actuaries, underwriters, and business stakeholders

• 6+ years as a Data Engineer
• Deep expertise in Databricks, PySpark, and Delta Lake architecture
• Advanced SQL and data modelling, including medallion/Lakehouse patterns
• Track record of owning end-to-end delivery with minimal oversight
• Strong CI/CD and DevOps practices in a data context
• Ability to make and communicate architectural decisions to both technical and business audiences
• English B2–C1 — leading stakeholder communication required

• Azure Data Services (Data Factory, Azure Storage, Azure SQL)
• Data governance, cataloguing, or Master Data Management
• Background in insurance, financial services, or risk management
• Experience with catastrophe modelling or reinsurance systems